System and Method of Workflow Management

ABSTRACT

Wireless systems and methods include a plurality of peripheral electronic devices each having a wireless communication system. A processor is configured to establish an association confidence level indicative of a likelihood that a peripheral electronic device is associated to a monitored subject for each peripheral electronic device based on association criteria. Indicators are configured to communicate the association the association confidence level.

BACKGROUND

The present disclosure is related to the field of workflow management.More specifically, the present disclosure is related to systems andmethod of managing workflow based upon an association between at leastone wireless sensor and a monitored patient.

Monitoring vital signs is an important part of patient care as thegeneral or particular health of the patient is determined, in part,through measurement and interpretation of key physiological indicators.Well-known parameters of patient health include blood pressure,hemoglobin saturation (SPO₂), and features of the electrocardiogram(ECG). However, the utilization of physiological instrumentation toobtain these measurements at the bed side of a patient also possesswell-known burdens to the clinical environment. The presence of cables,catheters, and tubing connecting the patient and sensors to theinstrumentation configured to provide all monitoring or therapeutic carecan diminish productivity and the quality of patient care. For example,rotating a patient to alleviate bed sores or patient ambulation aboutthe room can be problematic if the patient is saddled with tethereddevices. Procedural delays stemming from cable management alsocontribute to a great percentage of time dedicated to routine, mundanetasks not directly related to treatment of the patient's illness.

Wireless communication technology leveraged to patient monitoring andtherapy may at least mitigate some of the problems associated with cableclutter and device management. With instrumentation becoming wireless,the management of such devices is eased. In addition, wirelessinstrumentation/devices greatly reduce the burden associated with cablemanagement.

Wireless patient monitoring networks, however, bring new problems thatneed to be addressed for proper implementation of a monitoring regime.In many instances, whether using a wireless monitoring system or a wiredsystem, elements of the system communicate with at least one centralmanagement device. In the hospital environment, this management deviceis often used to relay monitored information to an infrastructure thatallows health care professionals to analyze the monitored informationfrom an outside location (e.g. a nurse station). In other wirelesssystems, the management device may be integrated with a centralprocessing unit that analyzes the incoming device information. Whencables are removed from these devices, a user of the system can nolonger safe guard that the devices are properly connected to the patientto be monitored by the management device by simply ensuring that thecables extend from the management device to the correct patient. Thatis, without cables, a health care provider or other operator lacks thevisual cues associated with cables to assure that the sensing devicesare properly connected to the proper patient to be monitored by themanagement device. Alternatively, as wireless sensing systemsproliferate in a care setting, wireless sensing devices mayinadvertently become communicatively connected with a management deviceassociated with another patient. Again, without the visual cues of thecable, a healthcare provider or other operator lacks a tool for fast andaccurate confirmation that the management device is receivingphysiological data from a specified patient and that patient only.

BRIEF DISCLOSURE

An exemplary embodiment of a wireless system includes a plurality ofperipheral electronic devices each having a wireless communicationsystem. A hub includes a wireless communication system. The hub is inwireless communication with the peripheral electronic devices. Aprocessor is configured to establish an association confidence level foreach peripheral electronic device based on a plurality of associationcriteria. The association confidence level for each peripheralelectronic device is reflective of the likelihood that a peripheralelectronic device is associated to a monitored subject. Each of aplurality of indicators are configured to communicate the associationconfidence level for a peripheral electronic device.

In an exemplary embodiment of a wireless patient monitoring system, aplurality of peripheral electronic devices each have a wirelesscommunication system and a sensor. Each of the plurality of peripheralelectronic devices is configured to be secured to a monitored patientand configured to acquire physiological data from the monitored patient.A hub includes a wireless communication system. The hub is in wirelesscommunication with the peripheral electronic devices to receive thephysiological data acquired by the peripheral electronic devices. Aprocessor is configured to register each of the plurality of peripheralelectronic devices to the monitored patient. The processor is configuredto receive the physiological data from the hub. The processor isconfigured to establish an association confidence level for eachperipheral electronic device. The association confidence level isindicative of a likelihood that the physiological data acquired by theperipheral electronic device is from the monitored patient. Each of aplurality of indicators is configured to communicate the associationconfidence level for a peripheral electronic device of the plurality ofperipheral electronic devices.

An exemplary embodiment of a method of workflow management in a wirelesspatient monitoring system includes providing a plurality of peripheralelectronic devices. Each of the plurality of peripheral electronicdevices includes a sensor configured to acquire physiological data froma patient and a communication system. A processor registers each of theplurality of peripheral electronic devices to a monitored patient.Physiological data acquired by each of the peripheral electronic devicesis received at the processor. An association confidence level isdetermined for each of the peripheral electronic devices based at leastin part upon the received physiological data. A perceptible indicationof the determined association confidence levels is produced.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an exemplary embodiment of a wirelesssystem.

FIG. 2 is a schematic diagram of an exemplary embodiment of a peripheralelectronic device.

FIG. 3 is a flow chart that depicts an exemplary embodiment of a methodof evaluating an association confidence level between a peripheralelectronic device and a monitored patient.

FIG. 4 is a flow chart that depicts an exemplary embodiment of a methodof responses to an association confidence level.

FIG. 5 depicts an exemplary embodiment of a graphical user interface inaccordance with an exemplary embodiment.

DETAILED DISCLOSURE

FIG. 1 is a schematic diagram of a wireless system 10. The wirelesssystem 10 includes a processor 12 that is configured in the manner asdisclosed herein to receive a plurality signals acquired by the wirelesssystem 10, evaluate the signals, and initiate a response. The wirelesssystem 10 further includes a hub 14 that is configured to communicateboth with the processor 12 and with a plurality of peripheral electronicdevices 16. It will be understood that in embodiments, the hub 14 may bean independent device that is communicatively connected to the processor12, while in other embodiments the hub 14 may be integrated into asingle device with the processor 12.

The hub 14 includes a wireless communication system 18 that exemplarilycreates a communication area or range 20 within which the hub 14 may becommunicatively connected with one or more of the peripheral electronicdevices 16 which similarly may comprise a wireless communication system22. It will be understood that the wireless communication systems 18, 22respectively of the hub 14 and the peripheral electronic devices 16 willbe communicatively compatible and in an embodiment are radio frequency(RF) wireless communication devices. However, it will be understood thatin alternative embodiments, the wireless communication systems 18, 22may include optical, magnetic, ultrasound, visible light, infrared, orother forms of wireless communication systems.

While embodiments of the peripheral electronic devices 16 may includeother components as described in further detail herein, each of theperipheral electronic devices 16 include at least one sensor 24 that isoperable to acquire or measure at least one parameter or signal. In thepresent disclosure, the exemplary embodiment and application of a healthcare setting is used for descriptive purposes, although, it will berecognized that alternative embodiments of the systems and methods asdisclosed herein may be used in conjunction with other applications inwhich a plurality of wireless peripheral electronic devices must bemanaged. Thus, in the exemplary embodiment given herein, the sensors 24may be physiological sensors that are configured to acquirephysiological data from a patient to be monitored 26. In non-limitingembodiments, the sensors 24 may include heart rate, pulse rate,temperature, electrocardiogram (ECG), blood pressure (e.g. NIBP),respiration, physical movement, electroencephalogram (EEG) and others asmay be recognized by a person of ordinary skill in the art.

In embodiments, the sensors of the peripheral electronic devices measureor otherwise acquire at least one physiological parameter from thepatient 26. The wireless communication system 22 of the peripheralelectronic devices works with the wireless communication system 18 ofthe hub 14 to wirelessly transmit the acquired physiological data 28from each of the peripheral electronic devices 16 through the hub 14 tothe processor 12.

The processor 12 is connected to at least one computer readable medium30. In embodiments, the processor executes computer readable code storedon the computer readable medium 30 as software or firmware. Theexecution of the computer readable code causes the processor 12 tooperate in a manner such as to carry out the operations and functions asdescribed herein. In an exemplary embodiment, the computer readablemedium is an integral part of the processor 12.

In still further embodiments, the processor is communicatively connectedto the at least one computer readable medium 30. Data is stored on thecomputer readable medium 30 such data may include information regardingsystem data, association criteria as described in further detail herein.In embodiments disclosed herein particular combinations of associationcriteria as may be used depending upon the patient, the peripheralelectronic devices used, or the patient diagnosis, etc., and/or a weightor priority assigned to one or more of the association criteria.

An input device 32 is further connected to the processor 12 wherein by aclinician or technician can enter information including informationregarding the patient to be monitored, the peripheral electronic devicesused, the physiological condition of the patient, the associationcriteria to be used in evaluation of the association between theperipheral electronic devices, or a weighting to be used in evaluatingsuch association criteria. In some embodiments as disclosed herein, theinput device 32 may be used by the clinician or technician to initiallyregister each of the peripheral electronic devices 16 to the patient tobe monitored 26. This initial registration may include the use of a barcode scanner or entering some other type of identifying information fromthe peripheral electronic device or the execution of a registrationprocess carried out by the wireless communication system 18, 22 of theperipheral electronic devices 16 and the hub 14, respectively.

The processor 12 further operates a graphical display 34 that visuallypresents an indication of the confidence level indicative of theassociation between each of the peripheral electronic devices and themonitored patient determined in a manner as described in greater detailherein. The graphical display 34 operates to present such information ina graphical user interface (GUI) which may be configured in a variety ofmanners to visually convey this information. In embodiments, thegraphical display 34 may be a flat panel display or may be a displayassociated with a laptop or tablet computer, or a display of a mobiledevice. In still further embodiments, the display 34 may have touchsensitive capabilities and as such operate as both the display 34 aswell as the input device 32. In still further embodiments, the display34 may further be operated by the processor 12 to present some or all ofthe physiological data acquired from the monitored patient by theplurality of peripheral electronic devices 16.

The processor 12 is further connected to an alarm 36. The alarm 36 maybe an audible or visual alarm that produces an alert indicative of theconfidence level in the association between each of the peripheralelectronic devices and the monitored patient. In an embodiment, thealarm 36 may only provide an indication when the confidence level in theassociation between a peripheral electronic device and the monitoredpatient falls below a predetermined threshold as determined by theprocessor 12. The alarm 36 may include a light indicator such as an LED;however, in alternative embodiments, the alarm 36 may be generated soundor a textual message sent to one or more care providers through textmessaging, e-mail or other known communication platforms.

In an alternative embodiment, the processor 12 further transmits asignal 38 indicative of the confidence level to each of the respectiveperipheral electronic devices 16 through the communication system 18 ofthe hub 14 and the respective communication system 22 of the peripheralelectronic device 16. Each of the peripheral electronic devices 16include an indicator 40 that operates to present the associationconfidence level received from the processor 12. In an embodiment, theindicator 40 may be a noise making device, a light emitting diode (LED)or other visual device, or a tactile device such as a vibration unitthat operates in a manner such as to notify a clinician or technician ofthe association confidence level in the association between theperipheral electronic device and the monitored patient. In onenon-limiting embodiment, the indicator 40 is a light source that isconfigured to emit light at an intensity level that is proportional tothe received association confidence level. In another embodiment, theindicator 40 is a light source, that is configured to emit light withina first color spectrum, exemplarily green if the confidence level isabove a first threshold, the light source emits light within a secondcolor spectrum, exemplarily yellow, if the confidence level is at orbelow the first threshold and above a second threshold, and emits lightwithin a third color spectrum, exemplarily red, if the confidence levelis at or below the second threshold. In such exemplary embodiments, thelight source may be one or more LEDs configured to emit light in therequired colored spectrum.

In a still further embodiment, the indicator 40 is an audible alarm thatis configured to emit an audible signal when the confidence level isbelow a predetermined threshold.

As will be described in further detail herein, in embodiments, theprocessor 12 may operate to provide an automated diagnosis or othertypes of automated medical guidance based upon the receivedphysiological data and other sources of information regarding thepatient, including, but not limited to the medical information found inthe patient's electronic medical record (EMR). Non-limiting examples ofsuch automated diagnosis or other automated medical guidance may includeautomated indications of the patient's condition based upon the acquiredphysiological data, suggested treatments, therapy, or recommendations tothe patient based upon the received physiological data. In one suchembodiment, the processor 12 provides the physiological data 42 acquiredby the peripheral electronic devices 16, the determined associationconfidence level 44 in the association between each of the peripheralelectronic devices 16 and the monitored patient 26, and the automatedguidance 46 as described above to the graphical display 34 forpresentation to the clinician. As will be described further therein, thepresentation of at least a portion of the physiological data and theassociation confidence levels in the acquisition of that physiologicaldata can help to facilitate a clinician's evaluations of any automatedlygenerated guidance based wholly or in part upon the receivedphysiological data. In alternative embodiments as described in furtherdetail herein, the automated guidance 46 may only be presented at thegraphical display 34 if the underlying physiological data is acquired atan association confidence level above a predetermined threshold that thephysiological data is associated with the monitored patient 26.

The processor 12 is further connected to data storage 48 wherein thedata storage 48 may be located on a computer readable medium that iseither local or remote from the processor 12. Thus, the data storage 48may be communicatively connected to the processor 12 through a localhospital intranet or a wide area network exemplarily over the Internet.In one embodiment, the data storage 48 is exemplarily an electronicmedical record (EMR) of the monitored patient and the processor 12 andreceives and stores the acquired physiological data 42 received from theplurality of peripheral electronic devices, the association confidencelevels 44 and any automated guidance 46 determined by the processor 12.

In an alternative embodiment as will be described in greater detailherein, the acquired physiological data 42 may be appended with thedetermined association confidence level 44 and the appended valuesstored together in the EMR.

In still further embodiments, the patient 26 is connected to at leastone therapeutic device 50 that provides therapy or treatment to thepatient. In embodiments, the therapeutic device 50 receives a controlsignal 52 from the processor 12. In response to the control signal 52,the therapeutic device 50 may take one or more automated therapeuticactions. The processor 12 generates the control signal 52 in part basedupon at least some of the received physiological data. In non-limitingembodiments, the therapeutic device 50 may be a defibulator, a drugpump, an intravenous (IV) solution pump, or a ventilator which mayoperate to provide an automated therapy to the patient in accordancewith the received control signal 52. In an exemplary embodiment, thedefibulator may perform an automated action upon detection of anarrhythmic pattern in the ECG waveform of the patient. In a furtherembodiment, a drug pump or IV solution pump may be delivered to increaseor decrease a rate of delivery of a medication or fluid in response to adetected change in physiological condition. In embodiments as will bedescribed in further detail herein, the processor may operate inconjunction with the determined association confidence levels for eachof the peripheral electronic devices that acquire the physiological dataand only produces a control signal 52 in order to initiate the deliveryof the automated therapy if the association confidence levels for theperipheral electronic devices that acquired the physiological data thatresulted in initiation of the automated therapy indicate a highconfidence level in being associated with the monitored patient who willreceive the automated therapy. In such embodiment, this safety featurehelps to ensure that if a peripheral electronic device becomes connectedto an alternative patient then the monitored patient, that alternativepatient's physiological parameters do not result in the delivery of anautomated therapeutic response to the wrong patient.

FIG. 2 depicts a more detailed exemplary embodiment of a peripheralelectronic device 54 such as may be used in conjunction with thewireless system 10 depicted in FIG. 1. The peripheral electronic device54 includes a processor 56 that executes software or firmware stored atthe processor 56 in order to carry out the functions as described infurther detail herein. The peripheral electronic device 54 furtherincludes a battery 58 that provides power to the processor 56 and othercomponents of the peripheral electronic device requiring energization,either directly or indirectly from the battery 58. In an embodiment, theperipheral electronic device 38 may be constructed such that the battery58 is replaceable or rechargeable. In such embodiments, the peripheralelectronic device 54 may be configured to be reused and the batteryreplaced or recharged in order to extend the life of the peripheralelectronic device 54. In other embodiments, the peripheral electronicdevice 54 may be disposable after the power is drained from the battery58. Depending upon such embodiments, the processor 56 may monitor eitherthe remaining battery life, elapsed time or elapsed usage since batteryreplacement or recharge, battery output voltage, or other suchmeasurement of remaining battery life.

As described above, the peripheral electronic device 54 is configured tobe secured to the patient to be monitored and to wirelessly transmitphysiological data 38 through an interaction between a wirelesscommunication system 18 of a hub 14, with a wireless communicationsystem 22 of the peripheral electronic device 16 (FIG. 1). In theexemplary embodiment of FIG. 2 the peripheral electronic device 54includes a transmitter 60 in order to broadcast or otherwise transmitinformation from the peripheral electronic device as described above,the transmitter 60 may include any of a variety of known communicationtransmitters, including, but not limited to radio frequency, infrared,visible light, or ultrasonic, or other known transmissionimplementations.

The peripheral electronic device 54 is configured with a sensor 62. Thesensor 62 is configured to acquire or otherwise measure a physiologicalparameter from the patient. Non-limiting examples of physiologicalparameters that may be measured or acquired, include biopotentials suchas electrocardiogram (ECG), electromyogram (EMG), andelectroencephalogram (EEG). The sensor 62 may also be configured toacquire other physiological parameters such a heart rate, oxygensaturation (SPO₂), blood pressure, such as acquired by noninvasive bloodpressure (NIBP) monitoring, respiration rate, motion detection, ortemperature. However, these are merely exemplary of the types of sensorsthat may be incorporated into the peripheral electronic device 54 andare not intended to be limiting.

Embodiments of the peripheral electronic device 54 may further include aposition detector 64. In an exemplary embodiment, the position detector64 may be a global positioning system (GPS) detector. The positiondetector 64 further provides the location of the peripheral electronicdevice 54 and can be transmitted by the transmitter 62 along with thephysiological data collected by the sensor 64.

The peripheral electronic device 54 may further include a clock 66 wherethe clock 66 may be a separate component found in the peripheralelectronic device 54, or may be an integral component associated withthe processor 56. In embodiments, the clock 66 can operate such as tomeasure an elapsed time since initial registration of the peripheralelectronic device 16 with the processor 12 FIG. 1 to the monitoredpatient as described above. In an alternative embodiment, the clock 66may be used to measure the operational time since the last batteryreplacement or recharge as also discussed above.

The peripheral electronic device 54 further may include an indicator 68connected to the processor 40. In embodiments, for notificationpurposes, the indicator 52 may be a noise making device, an LED or othervisual devices or a tactile device such as a vibration unit fornotifying a clinician or technician of the association status of theperipheral electronic device 54 with the monitored patient throughsound, light, or tactile methods.

FIG. 3 is a flow chart that depicts an exemplary embodiment of a method100 of evaluating an association between a peripheral electronic deviceand a monitored patient. The method 100 may be carried out by a wirelesssystem, such as wireless system 10 described above with respect to FIG.1; however, it will be understood that in alternative embodiments, anassociation confidence level can be determined in other ways. In anembodiment, association criteria of at least one system attribute and atleast one sensor attribute are evaluated to determine an associationconfidence level between the peripheral electronic device and themonitored patient. Depending upon the sensor itself, the type ofwireless communication system used by the sensor, and the componentsavailable in the peripheral electronic device (e.g. clock, positiondevice, as described above), certain system and sensor attributes asdescribed in further detail herein may be more relevant or applicable incalculating the confidence level. Alternatively, some associationcriteria may not be available due to the constraints of the peripheralelectronic devices, sensors, or the wireless system. As such, for anygiven system or monitored patient, a subset of the overall set ofpossible association criteria will exist.

At 102, each peripheral electronic device of the plurality of peripheralelectronic devices is registered to a monitored patient. It will berecognized that in the description herein, the peripheral electronicdevices registered at 102, may include a sensor and be configured to besecured to a patient and to transmit physiological data acquired by thesensor to a processor in the wireless system. As described above, theperipheral electronic devices may be registered by one or more clinicianor technician inputs into the wireless system in order to provide aninitial association between each of the plurality of peripheralelectronic devices and the patient to be monitored. Once the wirelesssensors are registered and secured to the monitored patient, theprocessor may begin to receive physiological data as acquired by thesensors through the wireless system.

At 104 system data are collected from the system. The system data arevalues and/or conditions that are related to the association of theperipheral electronic device to the monitored patient, but are a part ofthe wireless system rather than physiological data acquired from thepatient. Examples of association criteria that may be dependent uponsystem data collected at 104 can include length of time sinceregistration of a peripheral electronic device to a patient, an RFsignal strength, an elapsed time that peripheral electronic device isconfirmed off of a patient, activity types, a number of communicationerrors, a battery state or condition, a known operation lifetime of theperipheral electronic device, a location, exemplarily a GPS location, aproximity beacon, elapsed time on the patient, identified instances ofsensor disconnection from the patient, movement of the peripheralelectronic device, or a location of an accessory or other deviceassociated with the patient; however, these are merely exemplary of thetypes of association criteria that may be collected from the system.

At 106 physiological data acquired by the sensors of the peripheralelectronic devices are received by the processor. The peripheralelectronic devices transmit the physiological data to the processor asdescribed above through the wireless system. As further described above,a variety of physiological data may be acquired by sensors in peripheralelectronic devices associated to each patient. The receivedphysiological data may include, but is not limited to ECG, EMG, EEG,temperature, respiration, SPO₂, blood pressure, movement, heart rate,pulse rate, or others. Depending upon the diagnosis and treatment beingreceived by the patient, the patient may be monitored to acquire variousphysiological data. In embodiments, the acquired physiological data maybe in the forms of waveforms, traces, or other signals that must beprocessed to obtain values meaningful to determining an associationconfidence level.

At 108 association criteria values are derived from the physiologicaldata and the system data. The received physiological data is processedto derive association criteria values. The association criteria valuesderived from the physiological data may include such associationcriteria values that are representative of a confidence in theassociation status between an peripheral electronic device and themonitored patient by providing a measure of the coincidence or congruitybetween physiological data acquired between sensors of differentperipheral electronic devices in the plurality of peripheral electronicdevices.

In one example, a plurality of ECG leads may be acquired by separateperipheral electronic devices and an ECG signal, waveformcharacteristic, or heart rate as indicated by each of the ECG leads arecompared to determine whether each ECG signal is consistent orinconsistent with that obtained from the other leads. If the ECG signalobtained from one of the peripheral electronic devices is inconsistentwith the other ECG signals from the peripheral electronic devicesassociated with the monitored patient, then that peripheral electronicdevice will have a lower association criteria value to reflect thereduced confidence that that peripheral electronic device is associatedwith the monitored patient. Similar comparisons may be made acrossphysiological parameters, exemplarily, heart rate as determined throughECG signals acquired by peripheral electronic devices, and SPO₂peripheral electronic devices and an NIBP peripheral electronic devicemay all be compared to evaluate the consistency or inconsistency of theheart rates between each of these peripheral electronic devices toevaluate their association to the monitored patient.

In a still further embodiment, one physiological parameter measured by asensor of one of the peripheral electronic devices may produce a knownartifact in the signal acquired by a sensor of a peripheral electronicdevice configured to acquire another physiological parameter.Exemplarily, a known cardiac artifact may appear in any of a number ofphysiological parameter signals, including, but not limited to arespiration monitor, EEG waveform, or EMG waveform. Similarly, arespiration artifact may be known to be present in an acquired ECGsignal. In an alternative embodiment, the monitored physiological data,e.g. heart rate, as acquired from an ECG signal is compared to the knowncardiac artifact in the physiological data acquired by anotherperipheral electronic device and an association criteria value derivedto reflect this consistency or inconsistency, of this comparison betweenthe physiological data of the peripheral electronic devices.

In an embodiment, exemplary association criteria values derived fromsystem data may include a numerical representation of RF signal strengthor an association confidence based upon the length of time since theperipheral electronic device has been registered to the monitoredpatient. A further association criteria value may be a numericalrepresentation of a confidence that the peripheral electronic device isassociated with the patient to be monitored. For example, if the RFsignal strength of one peripheral electronic device is noticeably weakeror stronger than those of other peripheral electronic devices registeredto the same patient, this may indicate low confidence while congruencybetween all RF signals of the peripheral electronic devices registeredto the same patient may be a sign of increased confidence. Similarly, asthe length of time since the initial registration of the peripheralelectronic device, or length of time since a clinician's physicalverification of connection of the peripheral electronic device to themonitored patient gets longer, the confidence in the associationdecreases. Similarly, if a peripheral electronic device extends beyondan expected life, battery power, battery life, or recommendedreplacement time, these may all be indications of a lowered confidencein the association status. In other examples, if a sensor experiences alarge number of communication errors or is in a location apart fromother peripheral electronic devices registered to the monitored patient,these may be indicative of a reduced confidence in the associationstatus of the peripheral electronic device.

At 110 the association criteria are weighted. A weighting criteria isdetermined based upon the overall strength of each of the associationcriteria as well as the total number of association criteria availablein the subset of available association criteria. Weighting criteria mayalso be further determined based upon the derived values of theassociation criteria. As noted above, not all association attributes maybe used or available in all instances. Specifically, based upon thetypes of sensors or types of peripheral electronic devices and the typesand amount of physiological data collected, only a subset of thepossible association criteria will be available. The relative strengthof the association criteria in determining an association confidencelevel between a peripheral electronic device and a monitored patient maybe considered in weighting the association criteria. For example, anassociation criteria such as elapsed time since initial registration maybe heavily weighted if the elapsed time is short, but may receive alesser weighting as the elapsed time lengthens. In an embodiment, theweighting may again increase, as an indicator of decreased confidence,if the elapsed time exceeds an expected procedure duration or peripheralelectronic device expected usage. It is to be noted that in someembodiments only physiological data based association criteria may beused while in other embodiments a combination of association criteriabased upon system data and physiological data may be used. It ispossible that the number of association criteria changes and theweighting criteria changes during a single device-patient associationsession. As will be discussed in further detail herein, embodiments ofthe method 100 may be repeated periodically in order to produce anupdated evaluation of the association between the peripheral electronicdevices and the monitored patient and the weighting of the associationcriteria may change from cycle to cycle. These changes may be due to theaddition or subtraction of peripheral electronic devices, length of timeelapsing between evaluation cycles.

At 112 an association confidence level is determined for each peripheralelectronic device based upon the weighted association criteria values.In an embodiment, the weighted association criteria values are summed ona sensor by sensor basis. This summation may produce a raw indication ofthe association between each of the individual peripheral electronicdevices of the plurality and the patient to be monitored by thoseperipheral electronic devices. The association confidence leveldetermined at 112 may exemplarily be a normalized value of all of thesummed weighted association criteria values for that peripheralelectronic device. In an alternative embodiment, the associationconfidence level may be normalized on an S curve. Alternatively, anassociation confidence level may be exemplarily determined intocategories such as high, medium, and low association confidence level.This categorization may exemplarily be performed by comparing a rawassociation confidence level to a plurality of thresholds.

In embodiments, as mentioned above, the association confidence level foreach peripheral electronic device may be periodically recalculated suchas to update these determinations. In one embodiment, once anassociation confidence level has been calculated at 112 this previouslycalculated association confidence level may be used at 114 as anotherassociation criteria is weighted and incorporated back into the method100.

FIG. 4 is a flow chart that depicts an exemplary embodiment of a method200 of workflow management based upon an association confidence levelrepresentative of an association between each of a plurality ofperipheral electronic devices and a monitored patient. As reflected inthe method 200 a number of alternative responses or actions may be takenonce an association confidence level has been determined. Inembodiments, it will be recognized that one more of these responses mayoccur simultaneously or sequentially or that other types of responsesare also contemplated herein.

The method 200 begins at 202 when an association confidence level foreach peripheral electronic device is received. In an embodiment, theassociation confidence levels for each of the peripheral electronicdevices may be determined in the manner as explained above with respectto FIG. 3, although, in other embodiments, the association confidencelevel may be determined in other ways and still be used in the methodsas described herein.

In an embodiment, the association confidence levels for each peripheralelectronic device are compared to a plurality of thresholds in order tocategorize the association confidence levels and to direct workflowresponses. Exemplarily, the association confidence levels are comparedto a first threshold at 204 and a second threshold at 206.

At 204 the association confidence level is compared to a firstthreshold. This first threshold may exemplarily be representative of ahigh confidence in the association between that peripheral electronicdevice and the monitored patient. In a merely exemplary embodiment, theassociation confidence level is normalized on a scale of 0 to 100, thefirst threshold may exemplarily be a normalized score of 90 although thefirst threshold may be any value as deemed medically or institutionallyrelevant.

At 208 a visual indication of the confidence level may be presented,exemplarily as in any of the manners as disclosed above. As specificnon-limiting examples, the confidence level may be presented in agraphical user interface presented on a graphical display and suchpresentation may include both a presentation of the numericalassociation confidence level value and/or a categorization of suchassociation confidence level. FIG. 5 depicts a non-limiting example ofsuch a graphical user interface display 300. In still furtherembodiments, the association confidence level may be transmitted back toperipheral electronic device and a visual indicator, exemplarily one ormore light emitting diodes (LEDs) may be illuminated at a color orintensity representative of the association confidence level.

At 206 if the association confidence level is below the first thresholdat 204 then the association confidence level is compared to a secondthreshold. If the association confidence level is above this secondthreshold, the association confidence level may be exemplary denoted asa medium confidence and presented as described above with respect to208. In a non-limiting embodiment, the second threshold may be 70 on anormalized scale of 0-100, while in an alternative embodiment the secondthreshold may be 50 on a normalized scale of 0-100. If the associationconfidence level is not above the second threshold, then the associationconfidence level may be categorized as a low confidence in theassociation between that peripheral electronic device and the monitoredpatient, and such visual indication of the confidence level presented at208 as described above.

Additionally, if the association confidence level is below the secondthreshold, further actions may be undertaken in response to the lowconfidence in the association between the peripheral electronic deviceand the monitored patient. Exemplarily, an alarm may be indicated at210. The alarm may exemplarily be a visual, audio, or tactile alarm thatinitiated to alert a clinician or a technician of the reduced confidencein the association between the peripheral electronic device and themonitored patient. Such alarms may exemplarily be presented at agraphical user interface, at the peripheral electronic device, or maytake the form of a textual or other communication to a clinician ortechnician notifying them of the determined low confidence.

In an embodiment the alarm initiated at 210 is exemplarily directed orconfigured to prompt a response by a clinician or technician. In oneexemplary embodiment, the clinician or technician is prompted to locateand verify the physical placement and attachment of the low confidenceperipheral electronic device to the monitored patient. Such prompt mayinclude a prompt for the clinician or technician to reregister orotherwise verify that the peripheral electronic device is properlyattached to the monitored patient. This reregister or verification maybe used as or update a value of an association criteria, resulting in animproved association confidence level and removal of the alarm.

While the initiation of an alarm at 210 is depicted in FIG. 4 as beinginitiated only after the determination of a low confidence level, in analternative embodiment, there may be a plurality of states or stages ofconfidence level and various set alarms or alarms responses may escalatewith the escalation of the determined confident level.

A determination of a low confidence level may also result in thedisassociation of a peripheral electronic device from a monitoredpatient at 212. If the association confidence level is determined to bea low confidence, exemplarily below the second threshold at 206, thatperipheral electronic device may be disassociated from the monitoredpatient at 212. In such an embodiment, the physiological data obtainedby the peripheral electronic device may still be temporarily stored, butmay not be immediately entered into the patient's electronic medicalrecord or presented on a graphical display with the other physiologicaldata obtained from the monitored patient. This can be done as aprecaution such that physiological data in which there is a lowconfidence to have emanated from the monitored patient is notimmediately stored or presented in conjunction with the monitoredpatient. Since the confidence in this physiological data emanation fromthe monitored patient is low, in embodiments it may be preferable totake this precaution such that medical decisions, diagnosis, and othersuch determinations are not made based upon this physiological data. If,at a later time, the peripheral electronic device is verified to havebeen associated with the monitored patient at the time the data wasacquired, the physiological data may be restored to the patient'selectronic medical record. In an alternative embodiment, once theperipheral electronic device is disassociated from the monitoredpatient, the wireless system may no longer process or store anyphysiological data acquired by a wireless sensor of that peripheralelectronic device, until the peripheral electronic device isreregistered or verified as associated to the monitored patient.

At 214 the association confidence levels from 202 may be used in analternative manner such that the received physiological data from eachof the peripheral electronic devices is appended with the associationconfidence level for that peripheral electronic device at 214. Asdescribed above, the association confidence levels may be periodicallyre-determined at regular intervals and therefore the receivedphysiological data may be appended with the association confidence levelfor that peripheral electronic device in the time interval in which thephysiological data was acquired. This appended physiological data canthen be stored, exemplarily at the monitored patient EMR such that theappended physiological data can be later used in patient evaluation,diagnosis or therapeutic decisions as an additional piece of informationthat is reflective of the quality of confidence that the physiologicaldata was acquired by a peripheral electronic device that was actuallyassociated with the monitored patient.

Furthermore, in some wireless systems, the clinician or technician maybe provided with automated medical guidance or the patient may receiveautomated therapeutic interactions based upon the physiological dataacquired form the monitored patient. In an embodiment, the automatedactions may be desired to only be performed when there is a high levelof confidence between each of the peripheral electronic devices and themonitored patient. In such embodiments, at 216 the associationconfidence level for each of the peripheral electronic devices arecompared to a predetermined threshold. Similar to the threshold asdescribed above with respect to 204 and 206, this threshold mayexemplarily be a predetermined value based upon clinical standard for arequired confidence level. In a non-limiting embodiment, the thresholdat 216 may be a 95 on a normalized scale between 0-100, although this ismerely exemplary of the predetermined threshold that may be used. If oneor more of the confidence levels for each of the peripheral electronicdevices is below the predetermined threshold, then an alarm may beinitiated at 218 in order to alert the clinician or technician eitherthat automated actions are being taken without the requisite associationconfidence levels or to alert the clinician or technician that some orall of the automated actions have been disabled due to insufficientconfidence in the association between the peripheral electronic devicesand the monitored patient. If all of the confidence levels are above thepredetermined threshold, then automated actions may be taken based uponthe received physiological data from the peripheral electronic devices.The automated action may exemplarily include automated medical guidance,presented to the clinician or technician at 220. Automated medicalguidance may take any of a variety of forms, and specifically mayinclude identifications of potential physiological conditions or risksidentified based upon an analysis of at least in part, the acquiredphysiological data. In embodiments, the analysis may further extend todata stored in the patient electronic medical record, or other sourcesof medical data.

At 222 a further action that may be taken if the confidence levels areabove the predetermined threshold at 216 may be the operation andcontrol of an automated therapeutic interaction based upon the acquiredphysiological data. As described above, in some embodiments, therapeuticdevices such as IV or drug pumps, ventilators, or defibulators may beoperated to automatedly take a therapeutic action based upon theacquired physiological data. As these automated therapeutic interactionsmay have an adverse effect on the patient health or wellbeing if aninappropriate action is taken, it may be desirable in embodiments toonly provide such automated therapeutic interactions when there is ahigh confidence that all of the acquired physiological data analyzed toinitiate the automated therapeutic interaction has been acquired byperipheral electronic devices associated with the monitored patient.

In an alternative embodiment, automated therapeutic interactions mayoperate on a reduced functionality depending upon the peripheralelectronic device with the lowest association confidence level, and thatparticular level. In such an embodiment, basic adjustments or controlsmay be maintained at lower confidence levels, while more invasiveresponses may only be undertaken when there is a high confidence in allof the peripheral electronic devices. As a merely exemplary embodimentof an IV pump, under a lower confidence level, the IV pump may beoperated to maintain or make minor adjustment to an IV rate, whileautomated adjustments between intravenously delivered substances, or thedelivery of a bolus may only occur under a high confidence level witheach of the peripheral electronic devices.

As referenced above, FIG. 5 depicts an exemplary embodiment of agraphical user interface 300 that may be presented on a graphicaldisplay. The GUI 300 includes a plurality of sensor indicators 302. Thesensor indicators 302 may generally identify the anatomical location ofthe wireless sensor on the monitored patient. In an exemplaryembodiment, the sensor indicators 302 may be color coded to represent anassociation status of the sensor based upon the confidence value, suchassociation status may exemplarily indicate a high, medium, or lowassociation between the wireless sensor and the monitored patient. TheGUI 300 may further present the derived confidence value 304 associatedwith each of the wireless sensors. Thus, in embodiments such as thatdepicted in FIG. 5, a clinician or technician is presented with both avisual indication of a general association status as well as a moredetailed confidence value indication.

The functional block diagrams, operational sequences, and flow diagramsprovided in the Figures are representative of exemplary architectures,environments, and methodologies for performing novel aspects of thedisclosure. While, for purposes of simplicity of explanation, themethodologies included herein may be in the form of a functionaldiagram, operational sequence, or flow diagram, and may be described asa series of acts, it is to be understood and appreciated that themethodologies are not limited by the order of acts, as some acts may, inaccordance therewith, occur in a different order and/or concurrentlywith other acts from that shown and described herein. For example, thoseskilled in the art will understand and appreciate that a methodology canalternatively be represented as a series of interrelated states orevents, such as in a state diagram. Moreover, not all acts illustratedin a methodology may be required for a novel implementation.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to make and use the invention. The patentable scope of the inventionis defined by the claims, and may include other examples that occur tothose skilled in the art. Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral languages of the claims.

What is claimed is:
 1. A wireless system comprising: a plurality ofperipheral electronic devices each having a wireless communicationsystem; a hub having a wireless communication system, the hub inwireless communication with the peripheral electronic devices; aprocessor configured to establish an association confidence level foreach peripheral electronic device based on a plurality of associationcriteria, the association confidence level for each peripheralelectronic device being reflective of the likelihood a peripheralelectronic device is associated to a monitored subject; and a pluralityof indicators, each indicator of the plurality configured to communicatethe association confidence level for a peripheral electronic device. 2.The wireless system of claim 1, wherein the plurality of peripheralelectronic devices each have a sensor configured to measure aphysiological parameter, and the monitored subject is a patient.
 3. Thewireless system of claim 2, wherein the association criteria may bederived from the measured physiological parameters.
 4. The wirelesssystem of claim 1, wherein each of the plurality of indicators comprisea visible, audible, or tactile communication system.
 5. The wirelesssystem of claim 4, wherein each of the plurality of indicators comprisea light source configured to emit light at an intensity levelproportional to the confidence level.
 6. The wireless system of claim 4,wherein each of the plurality of indicators comprise a light sourceconfigured to emit light within a first color spectrum if the confidencelevel is above a first threshold, emit light within a second colorspectrum is the confidence level is at or below the first threshold andabove a second threshold, and emit light within a third color spectrumif the confidence level is at or below the second threshold.
 7. Thewireless system of claim 4, wherein each of the plurality of indicatorscomprise an alarm configured to emit an audible signal when theconfidence level is below a predetermined threshold.
 8. A wirelesspatient monitoring system, comprising: a plurality of peripheralelectronic devices each having a wireless communication system and asensor, each of the plurality of peripheral electronic devicesconfigured to be secured to a monitored patient and configured toacquire physiological data from the monitored patient; a hub having awireless communication system, the hub in wireless communication withthe peripheral electronic devices to receive the physiological dataacquired by the peripheral electronic devices; a processor configured toregister each of the plurality of peripheral electronic devices to themonitored patient, configured to receive the physiological data from thehub, and configured to establish an association confidence level foreach peripheral electronic device, the association confidence levelindicative of a likelihood that the physiological data acquired by theperipheral electronic device is from the monitored patient; and aplurality of indicators, each indicator of the plurality configured tocommunicate the association confidence level for a peripheral electronicdevice.
 9. The system of claim 8, further comprising a graphical displayoperated by the processor and the plurality of indicators are graphicaluser interface objects visually presented on the graphical display. 10.The system of claim 9, wherein the processor is further configured tocompare the association confidence levels to a predetermined threshold,and the processor initiates a response based upon the comparison. 11.The system of claim 10, wherein the processor initiates an alarm inresponse to at least one association confidence level being below thepredetermined threshold.
 12. The system of claim 10, wherein if theassociation confidence level for a peripheral electronic device of theplurality is above the predetermined threshold, the processor maintainsan association between the peripheral electronic device and theprocessor, and if the association confidence level for the peripheralelectronic device of the plurality is below the predetermined threshold,the processor disassociates from the peripheral electronic device. 13.The system of claim 10, wherein the processor is configured to operatethe graphical display to present automated medical guidance based uponthe received physiological data if the association confidence levels areabove the predetermined threshold.
 14. The system of claim 10, furthercomprising: at least one automated therapeutic delivery devicecommunicatively connected to the processor; wherein the processor isconfigured to operate the automated therapeutic delivery device toautomatedly provide a therapy to the monitored patient based at least inpart upon the received physiological data if the association confidencelevels are above the predetermined threshold.
 15. A method of workflowmanagement in a wireless patient monitoring system, the methodcomprising: providing a plurality of peripheral electronic devices, eachcomprising a sensor configured to acquire physiological data from apatient and a communication system; registering, at a processor, each ofthe plurality of peripheral electronic devices to a monitored patient;receiving physiological data acquired by each of the peripheralelectronic devices at the processor; determining an associationconfidence level for each of the peripheral electronic devices based atleast in part upon the received physiological data; producing aperceptible indication of the determined association confidence levels.16. The method of claim 15, wherein the perceptible indication is anindication visually presented on a graphical display.
 17. The method ofclaim 15, further comprising: comparing the determined associationconfidence levels to at least one predetermined threshold; andinitiating an alarm if at least one of the association confidence levelsfalls below the predetermined threshold.
 18. The method of claim 15,further comprising: appending the received physiological data with theassociation confidence level determined for the peripheral electronicdevice that acquired the physiological data; storing the appendedphysiological data at an electronic medical record of the patient. 19.The method of claim 18, further comprising: generating automated medicalguidance based at least in part upon the received physiological data;comparing the determined association confidence levels to at least onepredetermined threshold; and presenting the automated medical guidanceon a graphical display if all of the association confidence levels areabove the predetermined threshold.
 20. The method of claim 18, furthercomprising: controlling a therapeutic device based at least in part uponthe received physiological data to automatedly deliver therapeuticinteraction to the patient; comparing the determined associationconfidence levels to at least one predetermined threshold; andsuspending the automated delivery of the therapeutic interaction if atleast one association confidence level is below the at least onepredetermined threshold.